There is considerable interest in providing consumer electronic devices, including smart phones, computers, electronic tablets, and so on, with various means of securing information stored on these devices. Biometric security systems, such as fingerprint recognition systems, are one approach to providing these security features. These systems may not require memorization, or the use of any other device by the user, as security may be based on unique features of the user. They also provide the potential advantage being difficult to ‘crack’ for the same reasons.
Fingerprint recognition systems generally collect fingerprint images and compare those images against a database of known fingerprint information. For example, after a set of fingerprint images for a known authorized user is collected and processed, a user wishing access can be authorized by collecting one or more fingerprint images for that accessing user and comparing these collected images against known fingerprint information for the authorized user. One example of a fingerprint recognition system uses capacitive sensing elements to detect fingerprint images for collection. Such sensors are able to detect electric field differences between ridges and valleys of the fingerprint of a finger in contact with a contact surface of the consumer electronic device adapted for this purpose by measuring charge accumulated by the capacitive sensing elements.
In an example capacitive fingerprint sensor, these electric field differences are small compared to the total electric fields being measured and the charge accumulated is proportional to the total electric field. However, the signal produced by the capacitive sensing elements in such an example capacitive fingerprint sensor may include a relatively large fixed pattern signal that is based on the baseline carrier level accumulated by the capacitive sensing elements, even in the absence of a finger to image. This baseline signal is not based on the electric field differences of interest, but rather on parameters of the capacitive sensing elements.
Because the electric field differences of interest are very small, typically the signals detected by the capacitive sensing elements are amplified. However, amplifying the signals not only amplifies the difference signal of interest, but also amplifies the baseline signal of the capacitive sensing elements as well. Thus, any noise that is proportional to overall signal level generated during amplification may lead to a large fixed pattern noise component and significantly impact the signal to noise ratio of the fingerprint data.
The effectiveness of biometric security systems may be affected by the accuracy with which the unique biometric data on which they are based is able to be detected. In the case of fingerprint identification systems, this means that improved signal to noise ratios for detection of fingerprint data may lead to improved security for the secured device. Therefore, improving signal to noise ratios for detection of finger print data may be a significant issue in such systems.